According to a new study, people do. Even when they know that the advice is useless.

Researchers Nattavudh Powdthavee and Yohanes E. Riyanto investigated why people pay for advice about the future, particularly since the future is generally unpredictable (see our "Folly of Prediction" podcast on this topic). Their starting point:

Why do humans pay for advice about the future when most future events are predominantly random? What explains, e.g., the significant money spent in the finance industry on people who appear to be commenting about random walks, payments for services by witchdoctors, or some other false-expert setting?

I owe my favorite local bookstore, the Harvard Bookstore, for making another day for me. Wandering the tall, packed shelves on a warm and breezy evening, I ran across Schaum's Outline of Principles of Economics. One subtitle on the cover: "964 fully solved problems." The problems include, for example (from page 50): "True of false: As used in economics, the word demand is synonymous with need," or "True or false: A surplus exists when the market price is above the equilibrium price."

I didn't long much for either answer.

Instead, as the U.S. mortgage market has, as James Kunstlerpredicted on October 10, 2005, imploded "like a death star" and dragged "every tradable instrument known to man into the quantum vacuum of finance that it create[d]," as euros flee from Greece, and as bank loans dry up in Spain, I wished that the 964 fully solved problems included one or two of the real problems.

The same folks who stunned the world in 1972 with a prediction that economic growth would soon cease because of resource constraints are back again, predicting resource constraints will lead to global depression in 2030. Growth did not end by 1990, and it will not end in 2030. As before, prices will change to make economizing on increasingly scarce resources good business policy; and, as before, technology will change to lead businesses and consumers to substitute away from relatively scarce resources.

The interesting question is why this same nonsense continues to get so much attention. Is it that people forget the absurdities of the past arguments? Or do we have a substantial, never-satisfied demand for schadenfreude? Regardless, this stuff is just as bad economics as it was when The Limits of Growth first appeared.

Here’s something you don’t often hear an economist admit: We have very little idea where the economy will be next year.

Truth be told, our best guesses just aren’t very good. Government forecasts regularly go awry. Private-sector economists and cutting-edge macroeconomic models do even worse.

Our objective isn’t to beat up economists. Rather, we want to make the point that when we recognize our shortcomings, we’re forced to confront the enormous uncertainty that lies ahead. And appropriate humility about the economy changes how we think about policy.

Sports provide a powerful laboratory for social science research. In fact, they can often be a better place for research than real laboratories because sports provide a controlled setting in which people make frequent, real decisions, allowing for the collection of copious amounts of data. For instance, last summer, Daniel Hamermesh and colleagues used a database of more than 3.5 million pitches thrown in major league baseball games from 2004-2008 to identify biases in umpire, batter, and pitcher decision making. Similarly, Devin Pope and Maurice Schweitzer from the Wharton School used a dataset of 2.5 million putts by PGA golfers over five years to demonstrate loss aversion – golfers made more of the same-length putts when putting for par or worse than for birdie or better. Such studies tell us something about how we behave and make decisions in settings outside of sports as well.

Dan Johnson, an economist at Colorado College, has been predicting Olympic medal counts for years with a model that uses metrics like population count, income per capita, and home-country advantage. In the past six Olympics, his model has a correlation of 93 percent between predictions and actual medal counts, and 85 percent for gold medals.

For the Games in London this summer, Johnson predicts that the U.S. Will be the top medal winner, followed by China, Russia, then Britain -- the same order they finished in the 2008 Beijing Olympics.

The New England Patriots will win the Super Bowl by at least three points even though the New York Giants have the appeal of “a cocktail party stock,” according to a quantitative money management firm that’s correctly picked the team covering the point spread for eight consecutive years.

Analytic Investors LLC in Los Angeles has documented a tendency on the part of Super Bowl bettors to overestimate the chances of the team that rewarded them more during the regular season -- the team with the higher alpha, in investment parlance. In 2008, that was the favored Patriots, who lost to the Giants 17-14. This year, it’s New York.

“Everyone thinks the Giants are rolling right now, a lot of people in my office even,” said Matthew Robinson, a portfolio analyst for global and Japanese equities at Analytic and the author of this year’s analysis. “They like the Giants, but they have faith in the model as well.”

Our "Folly of Prediction" podcast included an interview with Joe Prusacki, who directs the statistics division at the USDA’s National Agricultural Statistics Service. This means he helps make crop forecasts (read a primer here). As hard as the USDA works, the fact is that predicting the future of even something as basic as crop yield can be maddeningly difficult. The Wall Street Journal has the latest in an article headlined "Erroneous Forecasts Roil Corn Market":

Government reports about the U.S. corn crop have become increasingly unreliable of late, contributing to wild swings in corn prices, a Wall Street Journal analysis shows.

Over the past two years, the Department of Agriculture's monthly forecasts of how much farmers will harvest have been off the mark to a greater degree than any other two consecutive years in the last 15, according to a Journal analysis of government data. This year's early-season forecasts also appear to have been way off. The next monthly report is due on Friday.